• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.127-131
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• 2007

The control of electrical appliances residing in the home network can be accomplished via Internet with the UPnP expansion without modifying an existing UPnP. In this paper, we propose the Internet Gateway that consists of an UPnP IGD(Internet Gateway Device) DCP(Device Control Protocol) and an UPnP Bridge as a system to control electrical appliances of home network. UPnP IGD DCP is to enable the configurable initiation and sharing of Internet connections as well as assuring advanced connection-management features and management of host configuration service. It also supports transparent Internet access by non-UPnP-certified devices. UPnP Bridge searches for local home network devices by sending control messages, while control point of UPnP Bridge looks up devices of interest on the Internet, subsequently furnishing the inter-networking controlling among devices which belong to different home network systems. With our approach, devices on one home network can control home electrical appliances on the other home network via Internet through IGD DCP with control commands of UPnP.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.542-545
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• 2005

본 연구에서는 Home Network System에서 가전기기들을 제어하고 집안의 상황을 원격지에 있는 사용자에게 전달해 줄 수 있는 Home Network Mobile Robot을 제작하여 보다 더 지능적이고 사용자에게 편리한 Home Network System을 구축한다. 이를 위해 본 논문에서는 실제 Home Network 시스템 하에서의 자율이동 로봇을 고안하였으며 이의 구동을 위해 OS로는 Linux Kernel 2.4를 Porting 하였고, Vision 및 Ethernet 통신이 용이하도록 회로를 설계, 제작하였다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.2
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• pp.100-108
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• 2014

In this paper, an idea of a network type distributed control of a system with inner loop control structure will be considered. Generally, in case of a control system with inner loop control structure, it is not easy to implement circuits and programming. Using network type distributed control structure, it will show how it is better than before. CAN(Controller Area Network) protocol which has been known that it has a high reliability on the signal in the various network protocols is used. Also, Arago's Disk System which has a inner loop control stucture is made to validate effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.476-479
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• 1992

This paper presents a neural network method for tuning PlD controller of a time-varying process. Three gains of PlD controller are tuned for a certain desirable response pattern by back-propagation neural network. The neural network is trained using changes of output features vs. changes of PlD gains. But sometimes it needs longer training time and larger structure to train the correlation between the process and controller on entire region of the process. The difficulty in system identification is that the inverse function of the system can not be clearly stated. To cope with the problem, we do not train the neural network to respond correctly for the entire regions but train for only local region where the system is heading toward by training the neural network and tuning of the PlD controller. It may be trained for fine-tuning itself. Simulation results show that the adaptive PID controller using neural network trained in the local area performs remarkably for time-varying second order process.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.554-565
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• 2012

In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2414-2416
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• 2003

In this raper, we present a Wavelet Neural Network(WNN) approach to the solution of the tracking problem for mobile robots that possess complexity, nonlinearity and uncertainty. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome the problems caused by local minima of optimization and various uncertainties. This network structure is helpful to determine the number of the hidden nodes and the initial value of weights with compact structure. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by the gradient-descent method. Through computer simulations, we demonstrate the effectiveness and feasibility of the proposed control method.

• Korea Trade Review
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• v.46 no.1
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• pp.113-134
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• 2021

This study analyzed the centrality of the GVCs network and the value-added-based production structure of the electrical and electronic industries using ADB-MIRO and social network analysis methods. According to the analysis, the centrality and power of the GVSc intermediate goods network were differentiated into China, the United States, and the EU due to the advancement of industrial structure in Asia. In the 2000 network, the United States and Japan had a very strong influence in all aspects, including connectivity and strength. However, in 2017, China's power index rose to number one among 62 countries in the network. Furthermore, this study presented strategic implications of the Korean electrical and electronic industries to respond to the reorganization of GVSs based on the analysis results.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.351-363
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• 2008

This paper is concerned with tasking and guidance of networked airborne sensors to achieve fault-tolerant sensing. The sensors are coordinated to locate hostile transmitters by intercepting and processing their signals. Faults occur when some sensor-carrying vehicles engaged in target location missions are lost. Faults effectively change the network architecture and therefore degrade the network performance. The first objective of the paper is to optimally allocate a finite number of sensors to targets to maximize the network life and availability. To that end allocation policies are solved from relevant Markov decision problems. The sensors allocated to a target must continue to adjust their trajectories until the estimate of the target location reaches a prescribed accuracy. The second objective of the paper is to establish a criterion for vehicle guidance for which fault-tolerant sensing is achieved by incorporating the knowledge of vehicle loss probability, and by allowing network reconfiguration in the event of loss of vehicles. Superior sensing performance in terms of location accuracy is demonstrated under the established criterion.

• ETRI Journal
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• v.42 no.5
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1796-1803
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• 2015

Unlike commercial LTE network, LTE-R railway network is arranged along a railroad track and the base stations of the network (RUs) are also installed on the waysides. For urban railway systems that are composed of underground tunnels, the leakage coaxial cables are widely used due to the radio propagation characteristics in tunnels. In theory, the tunnel sections are interpreted as the waveguide with blank spaces and for this reason, the tunnel sections are expected to be better than open ground sections in terms of the radio propagation characteristics. In this paper, we analyze the radio propagation characteristics based on this theory by replacing the leakage coaxial cables in the network with Yagi antennas. The test has been carried out in the 2.2km tunnel in the Daebul test track of KORAIL with 2.6GHz LTE-R Network. The LTE-R applicability in urban railways has been tested through the analysis on the radio propagation characteristics with the unmanned train operation system in Daebul tunnel.